Intapp, Inc. (INTA) Earnings Call Transcript & Summary

I'm Koji Ikeda. I'm one of the software analysts here at Bank of America. I am absolutely thrilled to have Intapp here today. We have a special guest, Thad Jampol. You are the Chief Product Officer, and you don't get out on the road all that much, so happy and thrilled to be able to do this with you. We also have Dave Morton, CFO. Thanks for joining us.

Thanks for having us.

Yes, absolutely. And so Intapp, vertical software business for professional services and financial services. I'm a big fan. I think what you guys do out there is great for all the different professional services, financial services organizations out there. But maybe for those in the room that are unfamiliar with Intapp and those on the webcast that are unfamiliar with Webtap (sic) [ Intapp ], maybe from a high level, what is the background of Intapp? You've been there for a long time. Tell us about the kind of the origin story there? And what are you guys doing right now? What is the opportunity that you're addressing?

Absolutely. And no, thank you again for having us. It's great to be here. For those that don't know, as you said, Intapp is a vertical industry cloud company focused on the financial and professional services industries. And we take a lot of inspiration from companies like Veeva, who build industry clouds for very specific, specialized industries. Our end markets are the large partnerships. So it's the large law firms, large accounting firms, large consulting, large investment banks, private capital firms and real asset investors. These are the industries that really drive the world's deals. And it's a surprisingly large industry, about 3% of the global economy, but these are partnerships. And so the business model, the operating requirements and the culture are just extremely distinct from other industries. And it's one of the reasons that we believe this industry has been underserved and overlooked by Silicon Valley historically. And you think about it, these organizations make deep foundational promises of trust and confidentiality to their clients, they hold a lot of the world's secrets. And so they're regulated in a way that no market is. They don't sell physical products or widgets or SKUs off of a price sheet that they compete based on knowledge, intellectual capital and these long-standing relationships. And structurally, they are mainly made up of professionals organized not by the traditional functional department but by area of expertise. And so we look at this and say, look, these are very, very profound differences and these industries, because of that, require hyper-specialized solutions and software, which is where Intapp comes in. And Intapp offers a very broad operating platform purpose-built for this industry. And it's made up of -- I'm the product guy. I talk about the product. So it's really made up of 4 main product lines. We have a solution that helps firms win new business by managing the complex web of deals and relationships and clients, investors and intermediaries. We have a solution that helps firms execute and deliver on that work collaboratively and efficiently. We have a solution that is a work to cash solution to ensure that these firms get paid for all their work and they could distribute maximum profits back out to the partners every year. And then we have a compliance suite that sits underneath everything to help them navigate the sort of complex set of compliance and regulatory obligations that they have.

Got it. It sounds like you got -- I mean, I know what you got. It sounds like you guys have a front office and back office platform for industries that are data-driven, trust-driven, knowledge-driven, which makes it difficult for horizontal vendors to be there not only from a -- well, let me ask you that question. I remember during the IPO period, we talked a lot about Salesforce, right? Salesforce [ hinted it ]. They have a horizontal solution that can do it, but maybe it's not the best solution or -- from a feature standpoint and then maybe from a cost standpoint. And so what are some of those things that the platform can do that makes it better, faster, more cost effective than something like a horizontal platform?

Yes, absolutely. And not coincidentally, you're going to see some dovetailing with the difference between AI from the horizontals versus vertical AI, but the answer is sort of the same. You come back down to starting with the data. And horizontal systems are really built for the manufacturing and retail worlds. They have very linear processes. And you think about just as an example, a typical transaction. There's a buyer. There's a seller. There's an asset or a SKU and there's a bunch of people around that on each side. But in this industry, there's co-investors. There's referring banks. There's lending syndicates. There's diligence teams. There's advising council. There's opposing council. And so all of these different stakeholders are critical to how these firms operate, and you need to be able to capture that so that you can reflect it back. And so I would put data as a big one. I think a second one is compliance. Again, I was talking about this. Compliance is existential to these organizations. Everything these professionals do is subject to conflicts or confidentiality or regulatory scrutiny or professional and ethical responsibility rules. It's not a check-the-box thing. It's not an after-the-fact bolt-on. And again, I'm probably jumping the gun here, but this is one of the big obstacles and encumbrances of this first wave of AI because it doesn't really think about the very profound compliance requirements and obligations that the clients set. And then thirdly is we are so intimate with the way that these workflows and processes happened as part of our industry orientation that that's a big one, understanding how are you augmenting and supporting these hyper busy professionals in the way that they work and within the tools that they work. And again, each of those 3, whether it's the data, the compliance obligations or sort of the workflows and processes, we just feel like we have a big advantage being so close to this market.

I know I've probably told John, your CEO, of this before, but I'm still waiting for the equity research CRM tool from you guys. I know that you guys do a lot of investment banking, kind of deal management with the DealCloud. But yes, when are you guys going to come out with the research product? Maybe a question for Dave. How do we think about the demand environment maybe split between broadly professional services and financial services? What does it look like today? How are you thinking about it for the future?

Yes. I mean I think our bigger context and some of the moves we made earlier this year with our go-to-market and looking at where some of the bigger opportunities were coming, before, we kind of weighted everything the same. Whereas what we talked about at our Investor Day, we saw over 70% of our SAM/TAM coming from the top 2,000-plus clients. And so that's where we kind of started over indexing on that go-to-market motion. And as a result, we've continued to see bigger pipe, win rates, a lot of strong deals come through that whole ecosystem, not only for this year, but then looking at this quarter, as what we talked about not only a couple of -- 1.5 months ago on our earnings call, but then even into FY '26, we are really excited about those opportunities. We'll be excited to talk to you all here at the end of the quarter as well as what that implies specifically for FY '26. So we believe everything that we've done as well as the rate of pace of innovation that Thad and his organization has brought on, we feel that we're positioned really nicely for how this company is continuing to deliver.

Okay. I'm going to start macro and kind of bring it in slowly down to vertical AI, but just starting macro. The demand environment within the categories that you're operating in, professional services, financial services, has been proven to be pretty resilient. Kind of IPO time, through the COVID ups and downs, the recessionary fears and even in today, you guys have been pretty darn good. What is it specifically about the professional services and financial services end market that really creates this nice end market?

Right. So I think it's a few things. I think first, we're very fortunate to have an incredibly stable end market. And even in sort of the down markets and as it fluctuates, you're going to pay your lawyers, you're going to pay your tax professionals, you're going to pay your auditors. And when you think about the private capital partners, they're getting paid at 2% out of their management fees, but it's from a fund that has a 5-, 7-, 9-year life span. So it's just -- it's long enough where they can weather whatever ups and downs there are there. I think secondly, there's just an inherent diversification in our markets. So a lot of these firms are made up of sub businesses of different practices or different service lines or different asset classes and strategies. And so we have seen in the past a shift in go-to-market and investment. So in a down market, you'll see accounting firms maybe move from advisory stronger into the audit side. You'll see firms move from some of the cyclical transaction work into more countercyclical litigation, restructuring bankruptcy work. Even the private equity, private capital firms, they're inherently diversified because they have portfolios of different assets underneath that. So there's diversification. And then lastly, I'd call out and perhaps counterintuitively, and we've seen this going through the 2008-2009 financial crisis and COVID, that firms when you take the foot off the pedal a little bit in the go, go, go, deal, deal, deal side, they have a moment to go enhance their operation to go make some investments that they've wanted to do for a while, and they'll spend in the areas that they deem strategic even while they're reducing and cutting some of the ancillary areas. And we've been very fortunate to be deemed within those strategic categories. And we've done some of our biggest deals in the depths of financial crisis or COVID.

Let's move to AI. We'll start macro on AI. Tell me a little bit about why vertical AI is maybe differentiated from horizontal broad AI?

Yes. So I touched on some of this earlier, but we talk to our customers a lot, but there's 2 particular moments that I think are really illustrative. So in the beginning of the year, we have a CIO Advisory Board that we host in Redmond together with Microsoft, and we invite a few dozen of the most influential innovative CIOs, and we talk there. And then follow that, we have an event we call the Ambassador Event where we invite some of our biggest power users. And when we had these sessions last year 2024, there is a lot of optimism on the first wave of this generative AI as we were talking about mostly from the horizontals because they were early out of the gates. They were piloting. They were trialing it. When we got together this year, the tenor was very different, that they felt that while a lot of this technology had cool aspects to it, that had potential, it ultimately didn't deliver the outcomes they were looking for. And I do think it comes down to those 3 things. At least, this is what I'm being told, is that it's not using the firm's data. Like these models are so powerful and they're incredibly innovative and we're excited about them, but at their core, they're inherently generic. Their raw technology trained from information across the broad Internet, and that is part of its power, but the broad Internet doesn't understand the precision of the deals and the transactions and litigations that these professionals work on every day. And so it just -- it didn't use their data. Secondly, a lot of the General Counsel's office and compliance offices just put the brakes on these when they started panicking about the oversharing risks that these copilots and models might introduce into these firms that have -- they have MNPI. They have PII. They have trade secrets. They have comp information all over the place. And a lot of these first wave of innovations didn't really consider the implications of that. And then thirdly, and I think this is probably the biggest one, is the professionals never really adopted en masse the tools that came in. And so I think this is because these initial waves of generative AI are -- they're separate panes of frames that sit on the side of your screen. They're blank with a blinking cursor. We joke that it feels like MS-DOS. They just sit there and they ask you to type in something inspirational or something really important and you get natural language back out. But it puts this incredible cognitive burden on these very, very busy professionals, and it's asking them to context shift away from the other applications and working on the deals and working with their clients and fighting their competitors and developing prospects to jump over to this other screen that's blank, enter something, get the results, find a way back into your application and your workflow. So those areas, I think people were very suspect of. They've shifted their focus now much more practically into more vertical AI, to your point, and they're really focusing on grounding the data within the firm's proprietary information, having a compliance confidentiality-first offering and ensuring that the AI is manifested directly within the workloads and the processes and the productivity tools that the professionals are using every day.

Is the thought process here within your industries a blinking cursor ChatGPT screen, how can I help you is not how can I help you because -- the cognitive burden that you've [ been seeing ]? How do you bridge that, from the offerings that you have that are -- or something where I'm afraid to put something in here because I don't know what's going to happen with the sensitive data in compliance and everything? How do you make that easier, more digestible for you?

So I'll answer that in 2 ways, starting with the end of that, which is the -- how do you have confidence, trust that all this AI is going to be compliant and work with what you're doing. So the first thing to do is to ensure that all of your information is protected. And it sounds fairly straightforward to do but all of these innovations from Microsoft and the productivity tools, which are incredible, all the Teams and the OneDrive and all the M365, they're collaborative. They make it so easy to unintentionally do something that reveals or shares sensitive information. You need to counter to that. And that's an area that Microsoft and Intapp have worked together on. It's in our mutual interest. And so we have a confidentiality solution that we call Walls for AI. And we launched it on stage last -- or one of our big shows, and we had the Head of Copilot on stage with us. And it really looks at the overall sort of data landscape and identifies where sensitive information is, is it protected, is it not protected, and then the Walls product is a centralized place that can enforce the right confidentiality policies across all the different systems. So that's sort of the first part of your question. The second part of your question is how do we bridge this gap from the blinking cursor, and this is where it gets really exciting. So if you look across a lot of our applications, I'll pick a few out of the air. You look at time. We have a Time product that helps essentially lawyers track their time and ensure that they get the bill out of this. We use AI to capture it. And we could embed right there in the application, we can tell you all the time that you worked. We can tell you what your time sheet is. You can now talk to it. It will build out a narrative. The AI will figure out if that narrative is actually a good narrative. And if it conflicts or violates any commitments you've made to clients, it will tell you. Then it will suggest changes to it. It's right there in the application. You don't need to go anywhere else. In our Conflicts, conflicts of interest product, so a lot of these firms, before bringing on a new piece of work, you have to go through a fairly rigorous process to ensure that you're not representing somewhere the opposite side of a deal or a litigation or something like that. And we have AI embedded right there that will say, "Based upon the way this firm operates and what we've seen from other organizations where risks -- here are the areas that you might want to double click on and spend some additional time because we think there might be something riskier." Or within DealCloud, within our product that allows you to go win more business, we can embed right there capabilities, allowing you to go see all of these exciting opportunities that you might invest in based upon your historical investments. So the list goes on and on. The point to take away here is that it's embedded directly within these applications in context at the moment that you need it.

So it sounds like you guys are doing all the right things with AI. I'm going to put my more balanced hat on for a second. And so what's the catalyst for your customers to adopt this stuff? What are they waiting for? Are they still waiting? I mean how do we think about what gets them to start really buying this stuff?

Yes. So surprisingly, or maybe not surprisingly, a lot of people here probably work at a firm within this industry that they -- these industries have been a little slower in the core of digitalization and the digital transformation. And a lot of the trends that we've seen of moving to the cloud and other industries are still happening right now in this market. We're working with a ton of organizations and helping them move their older on-premises, in-house-built tools over to our modern cloud and SaaS solutions, and that is a big demand generator for us. But then on top of that, what really gets them excited is that, that is an enabler of generative AI because you have to be in the cloud really in order to take advantage of this. And they, like we, are huge believers and very bullish on the potential transformative opportunities of generative AI in the way you operate and compete. And so we're seeing this opportunity and this demand generation for both the cloud and then the generative AI on top of that. And then compliance, the third one, again, very existential to this industry, and they want to get it right, and they also see the yin and the yang between having the right compliance and confidentiality underpinnings, allowing you to bring in all of this generative AI and be able to take advantage of it in a safe and trusted way.

Throughout your answers, Thad, you mentioned Microsoft. You mentioned Seattle. I know you guys have a big partnership with them. But maybe for those in the audience and those on the webcast that are unfamiliar with your partnership with Microsoft, tell us about it. How deep is it? And where is that going in the future?

Sure. Yes. So it's about 3 years in right now. And I would -- there are many pieces to it, but I would call out really 2 big pieces. The one that gets our clients most excited is the co-innovation side of this. And we -- every year that has gone by, we've gotten closer and closer to the engineering teams. We're talking to them regularly. We're co-innovating in a number of areas. I talked about Walls for AI. That's a very important one. We really are looking to make sure that all of our innovations, again, to this blinking cursor point, meet professionals where they are today, and they're not just requiring this big context shift. One of the places where a lot of professionals are in our industry is in M365 and the Office Suite. So we have a lot of initiatives together with Microsoft to be able to natively plug right into Teams or right into Copilot. So we have a lot of progress there, and we share a lot of it in our big Redmond meeting, and that's really exciting. We're also really excited about the go-to-market and the co-selling together with that. So Microsoft has these Microsoft Azure minimum commitment agreements, spend agreements. They're called MAC agreements. And what's really, really great, because we are in the top tier of their partnership, is that firms will get dollar-for-dollar credit against their committed Microsoft spend buying Intapp products. And so we actually just had a really, really big account who was kind of on the fence between buying -- on buying DealCloud, say, "Oh, I could use the MAC spend because your product is in the Azure marketplace. It's essentially free for me if you've got that dangling out there." So in certain situations, it's been a real catalyst and an accelerant of deals. And all of these firms and all of them are industries that we serve are very heavy Microsoft users.

Okay. Okay. Tell me about Amplify, kind of a big event that you guys had, lots of big announcements. I watched it, but I'd love to hear kind of your view and some of the big announcements within that?

Sure. We're really, really excited by that. So Amplify is the name of our big annual customer event. It's very heavily product oriented. We share a lot of R&D, a lot of our innovation. We make a number of big product and SKU announcements there. It's held in New York. Last Amplify in 2024, we announced our Intapp Assist brand, which is our generative AI brand, and we launched our Assist for DealCloud SKU. We're really, really excited about the uptake that's had in the market, and then we follow that up with a number of other Assist in our product line SKUs. This Amplify, which we just had in February, we doubled down on AI. And we made a number of, I think, really, really exciting announcements that went over really, really well with our market. And just to give you a few examples. We announced Assist smart tags. Assist smart tags uses AI to analyze all the conversations and call notes and meeting transcripts that happen throughout the day within these organizations and then to be able to identify the interesting nuggets of intelligence and then bring them to the relevant stakeholders instantly there. And so this is critical because you think about how many of these conversations happen every day, these are relationship-based businesses. So the number of calls and meetings, I mean, it's hundreds or thousands every day. And then the insights, the competitive intelligence, the opportunities that get buried in this unstructured data, these call notes that just sit in the system and never see the light of day, it's incredible. And so what smart tags is able to do is go in there and find it and bring it to the right professionals so that they can be smarter in front of their prospects, they could find more opportunities and they could have that extra advantage against their competitors. So that's smart tags. We announced Assist Prompt Studio. Prompt Studio allows you to get very granular in the configuration of prompts and how generative AI is surfaced within the application. A great example that I just heard is there's a firm. This was a sort of a well-known middle market private equity firm. And they really wanted to focus on the reciprocity of their advisers, meaning they're spending a lot of fees with their advisers, and they want to make sure their advisers are bringing them leads back. And so they configured the prompt. I just checked it earlier and they're able to say, "Show me right on the Advisers page -- when I load it up in DealCloud, I want to know the total amount of fees that we spent with this adviser. I want to know how many sell-side leads they brought me. I want to know how many of those leads converted opportunities, and I want to know how many of those opportunities we actually worked. And then I want the AI to summarize the health of our relationship with this adviser." It's a great example of what Prompt Studio can do. We've also seen firms who will want their growth equity partners to really see different information highlighted about companies, so cap tables, growth rate, CAGRs. They'll want to see the private credit team. They're going to be more interested in EBITDA and free cash flows and debt service credit ratios, those types of things. So that's Prompt Studio. We announced Assist origination. This was a big one for us. Assist origination uses AI to go find and source the best new opportunities for a fund or a firm. And there's $3.7 trillion of dry powder that these firms have to go commit and deploy. And we think the winners are going to be the ones who are most able to go directly source the best new platform acquisition or add-on acquisition faster than their peers. And the magic of this is the data. And we bring together all of this private company information from across the Internet that we use delphai, a company we acquired a few years ago, to do. We combine that with a lot of firmographic data feeds that firms use through third-party subscriptions and then firm's proprietary data itself within DealCloud. Have I met with this company? Have I done workups or models? Have I made bids? And it's all surfaced directly in DealCloud. So it's just right out of the bat integrated with all your workflows, your pipeline, your Monday morning meetings, your investor committee preparation. So you get this incredible force multiplication effect of coverage, sourcing BD teams of 25, 30 being able to do the work of 40 or 45. And then we had a time for AI. I talked about that. We had Walls for AI. I talked about that. It was -- there was just a lot of AI top to bottom. We introduced about a half dozen additional monetized AI SKUs.

Wow. Just listening to that, I would love to have Assist smart tags for equity research. So if you could do that, I would love that. Throw that in there with equity research CRM.

I didn't know this is a pipeline generation event.

That all sounds great. And so how are you guys differentiated? Or how are you going to keep this differentiated from the competition? Because I think about 2 things. One, clearly, professional services, financial services, good growth. I mean you guys show great growth in your SaaS. SaaS numbers, cloud ARR, I mean, good numbers there. And so I always fear that people will -- the horizontal vendors might recognize this and come after you. And so then it becomes product, right? Product will win. So talk to me a little bit about why your product is differentiated today and how is it going to continue to be differentiated?

Well, it's a great bookend question. I opened with sort of the company, and you had asked about some of the company's beginnings. And when we started the company and we bootstrapped it and we got into law firms very quickly. The law firm that was doing our patent work looked at our product and said we should have this. And we hired their CIO as our first seller, and they brought us into a lot of this very insular self-referencing community. And what was so serendipitous for us is that we were middleware at that time. We were integration, and we didn't see just one application area that we really understood the whole application landscape, and we understood more importantly, the data model. And so that was the formative start of really building what we call the industry graph data model. We think this is one of our big innovations and one of our long-term durable technology moats. And it really is -- reflects the way that these industries and professionals work, and we can capture that information that the AI so desperately needs. I use that example of sort of a transaction. That's an example of that. And because of this industry graph data model, you could answer these big strategic questions, which are not new, by the way. They've been out there for a while, but no one's been able to really do this. It's sort of like what business and what segments have I been most commercially successful so I could do more of that? Or who in my network has more influence or referred work to me so I could spend more time with them? Where are the best deals for my fund? What is the likelihood of transaction? And what is my best path of introduction, so I have first-mover advantage? Or where are the best follow-on work or cross-sell opportunities so I can develop my clients? And all of that is based upon having this incredible industry graph data model, which I don't think one of these horizontals can do anytime soon.

Got it. Maybe the last question here, and David, I didn't forget about you.

No worries.

I wanted -- you guys are clearly in an attractive growth category. And so as the CFO, how do you think about balancing growth versus profitability? I mean, you guys showed great margin expansion. But does that continue forever? Are you going to invest more? How do you think about it?

Yes. I mean we've shown really good diligence and judiciousness. I think it goes back to the culture of being bootstrapped. And so this wasn't a company that was born out of endless funding and then all of a sudden had to get profitable here in the 2020s. And so we are very thoughtful and we'll continue to apply economics towards Thad and his organization to keep that competitive moat out there. We'll continue to drive productivity within our sales and marketing and absolute reductions in G&A. We've done things with our services model. There could be some room to go there. But all things being considered, yes, we really like of how we framed up on '25. We like our long-term model. We think it's within near reach than not. Almost time for another Investor Day, might you say. And so yes, we're just really excited about those opportunities. And when you think about some of the returns that we're getting, both on the AI products we're doing, it's hard to say why we wouldn't continue to invest while also contributing to the bottom line.

Got it. Yes. I like that near comment. And so we'll leave it at that. Thank you guys so much. Fun conversation. Thanks so much for coming.

Thanks for having us, Koji.

Thank you.

Thank you.